Abstract
This paper presents a methodfor comparing a student essay andthe text of a course. We first show that the comparison of complex semantic representations is better done with sub-symbolic formalisms than symbolic ones. Then we present a methodwhic h rely on Latent Semantic Analysis for representing the meaning of texts. We describe the implementation of an algorithm for partitionning the student essay into coherent segments before comparing it with the text of a course. We show that this pre-processing enhances the semantic comparison. An experiment was performedon 30 student essays. An interesting correlation between the teacher grades and our data was found. This method aims at being included in distance learning environments.
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Gounon, P., Lemaire, B. (2002). Semantic Comparison of Texts for Learning Environments. In: Garijo, F.J., Riquelme, J.C., Toro, M. (eds) Advances in Artificial Intelligence — IBERAMIA 2002. IBERAMIA 2002. Lecture Notes in Computer Science(), vol 2527. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36131-6_74
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DOI: https://doi.org/10.1007/3-540-36131-6_74
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